Human Face Recognition Using Third-Order Synthetic Neural Networks
By: by Okechukwu A. Uwechue, Abhijit S. Pandya
Contributors: Pandya, Abhijit S.
Series: The Springer International Series in Engineering and Computer Science, Multimedia Systems and Applications -- 410; Springer International Series in Engineering and Computer Science, Multimedia Systems and Applications -- 410.
Publisher: Springer US
Published: 1997
Place of publication: Boston, MA
Language: eng
Format: [electronic resource] /
Number of pages: 123
ISBN-13: 9781461368328; 9781461540922
Subjects: Multimedia systems; Computer vision; Computer science
Description: Human Face Recognition Using Third-Order Synthetic Neural Networks explores the viability of the application of High-order synthetic neural network technology to transformation-invariant recognition of complex visual patterns. High-order networks require little training data (hence, short training times) and have been used to perform transformation-invariant recognition of relatively simple visual patterns, achieving very high recognition rates. The successful results of these methods provided inspiration to address more practical problems which have grayscale as opposed to binary patterns (e.g., alphanumeric characters, aircraft silhouettes) and are also more complex in nature as opposed to purely edge-extracted images - human face recognition is such a problem. Human Face Recognition Using Third-Order Synthetic Neural Networks serves as an excellent reference for researchers and professionals working on applying neural network technology to the recognition of complex visual patterns.
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